520 lines (520 with data), 195.2 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "2a324432-ce09-45e9-a9d5-f06f24120495"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696870882.7412632\n",
"Mon Oct 9 17:01:22 2023\n"
]
}
],
"source": [
"# This cell is added by sphinx-gallery\n",
"# It can be customized to whatever you like\n",
"%matplotlib inline\n",
"# !pip install pennylane\n",
"\n",
"import time\n",
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "4d4762dd-e1ad-499f-a5c2-7a069ddb930e"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"import pennylane as qml\n",
"from pennylane import numpy as np\n",
"from pennylane.optimize import AdamOptimizer, GradientDescentOptimizer\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"# Set a random seed\n",
"np.random.seed(42)\n",
"\n",
"\n",
"# Make a dataset of points inside and outside of a circle\n",
"def circle(samples, center=[0.0, 0.0], radius=np.sqrt(2 / np.pi)):\n",
" \"\"\"\n",
" Generates a dataset of points with 1/0 labels inside a given radius.\n",
"\n",
" Args:\n",
" samples (int): number of samples to generate\n",
" center (tuple): center of the circle\n",
" radius (float: radius of the circle\n",
"\n",
" Returns:\n",
" Xvals (array[tuple]): coordinates of points\n",
" yvals (array[int]): classification labels\n",
" \"\"\"\n",
" Xvals, yvals = [], []\n",
"\n",
" for i in range(samples):\n",
" x = 2 * (np.random.rand(2)) - 1\n",
" y = 0\n",
" if np.linalg.norm(x - center) < radius:\n",
" y = 1\n",
" Xvals.append(x)\n",
" yvals.append(y)\n",
" return np.array(Xvals, requires_grad=False), np.array(yvals, requires_grad=False)\n",
"\n",
"\n",
"def plot_data(x, y, fig=None, ax=None):\n",
" \"\"\"\n",
" Plot data with red/blue values for a binary classification.\n",
"\n",
" Args:\n",
" x (array[tuple]): array of data points as tuples\n",
" y (array[int]): array of data points as tuples\n",
" \"\"\"\n",
" if fig == None:\n",
" fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
" reds = y == 0\n",
" blues = y == 1\n",
" ax.scatter(x[reds, 0], x[reds, 1], c=\"red\", s=20, edgecolor=\"k\")\n",
" ax.scatter(x[blues, 0], x[blues, 1], c=\"blue\", s=20, edgecolor=\"k\")\n",
" ax.set_xlabel(\"$x_1$\")\n",
" ax.set_ylabel(\"$x_2$\")\n",
"\n",
"\n",
"Xdata, ydata = circle(500)\n",
"fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n",
"plot_data(Xdata, ydata, fig=fig, ax=ax)\n",
"plt.show()\n",
"\n",
"\n",
"# Define output labels as quantum state vectors\n",
"def density_matrix(state):\n",
" \"\"\"Calculates the density matrix representation of a state.\n",
"\n",
" Args:\n",
" state (array[complex]): array representing a quantum state vector\n",
"\n",
" Returns:\n",
" dm: (array[complex]): array representing the density matrix\n",
" \"\"\"\n",
" return state * np.conj(state).T\n",
"\n",
"\n",
"label_0 = [[1], [0]]\n",
"label_1 = [[0], [1]]\n",
"state_labels = np.array([label_0, label_1], requires_grad=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NqAg65FbTnyx"
},
"source": [
"Simple classifier with data reloading and fidelity loss\n",
"=======================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"id": "ZyKIWD9bTnyx"
},
"outputs": [],
"source": [
"dev = qml.device(\"lightning.qubit\", wires=1)\n",
"# Install any pennylane-plugin to run on some particular backend\n",
"\n",
"\n",
"@qml.qnode(dev, interface=\"autograd\")\n",
"def qcircuit(params, x, y):\n",
" \"\"\"A variational quantum circuit representing the Universal classifier.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): single input vector\n",
" y (array[float]): single output state density matrix\n",
"\n",
" Returns:\n",
" float: fidelity between output state and input\n",
" \"\"\"\n",
" for p in params:\n",
" qml.Rot(*x, wires=0)\n",
" qml.Rot(*p, wires=0)\n",
" return qml.expval(qml.Hermitian(y, wires=[0]))\n",
"\n",
"\n",
"def cost(params, x, y, state_labels=None):\n",
" \"\"\"Cost function to be minimized.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): array of state representations for labels\n",
"\n",
" Returns:\n",
" float: loss value to be minimized\n",
" \"\"\"\n",
" # Compute prediction for each input in data batch\n",
" loss = 0.0\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" for i in range(len(x)):\n",
" f = qcircuit(params, x[i], dm_labels[y[i]])\n",
" loss = loss + (1 - f) ** 2\n",
" return loss / len(x)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3Bz83H0xTnyx"
},
"source": [
"Utility functions for testing and creating batches\n",
"==================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"id": "i1-TLseuTnyx"
},
"outputs": [],
"source": [
"def test(params, x, y, state_labels=None):\n",
" \"\"\"\n",
" Tests on a given set of data.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" predicted (array([int]): predicted labels for test data\n",
" output_states (array[float]): output quantum states from the circuit\n",
" \"\"\"\n",
" fidelity_values = []\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" predicted = []\n",
"\n",
" for i in range(len(x)):\n",
" fidel_function = lambda y: qcircuit(params, x[i], y)\n",
" fidelities = [fidel_function(dm) for dm in dm_labels]\n",
" best_fidel = np.argmax(fidelities)\n",
"\n",
" predicted.append(best_fidel)\n",
" fidelity_values.append(fidelities)\n",
"\n",
" return np.array(predicted), np.array(fidelity_values)\n",
"\n",
"\n",
"def accuracy_score(y_true, y_pred):\n",
" \"\"\"Accuracy score.\n",
"\n",
" Args:\n",
" y_true (array[float]): 1-d array of targets\n",
" y_predicted (array[float]): 1-d array of predictions\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" score (float): the fraction of correctly classified samples\n",
" \"\"\"\n",
" score = y_true == y_pred\n",
" return score.sum() / len(y_true)\n",
"\n",
"\n",
"def iterate_minibatches(inputs, targets, batch_size):\n",
" \"\"\"\n",
" A generator for batches of the input data\n",
"\n",
" Args:\n",
" inputs (array[float]): input data\n",
" targets (array[float]): targets\n",
"\n",
" Returns:\n",
" inputs (array[float]): one batch of input data of length `batch_size`\n",
" targets (array[float]): one batch of targets of length `batch_size`\n",
" \"\"\"\n",
" for start_idx in range(0, inputs.shape[0] - batch_size + 1, batch_size):\n",
" idxs = slice(start_idx, start_idx + batch_size)\n",
" yield inputs[idxs], targets[idxs]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "B5s1nRL2Tnyy"
},
"source": [
"Train a quantum classifier on the circle dataset\n",
"================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "db0e55ad-567a-41eb-d0e8-983a87702f53"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.415535 | Train accuracy: 0.460000 | Test Accuracy: 0.448500\n",
"Epoch: 1 | Loss: 0.148371 | Train accuracy: 0.780000 | Test accuracy: 0.718000\n",
"Epoch: 2 | Loss: 0.135074 | Train accuracy: 0.815000 | Test accuracy: 0.794500\n",
"Epoch: 3 | Loss: 0.130469 | Train accuracy: 0.845000 | Test accuracy: 0.797000\n",
"Epoch: 4 | Loss: 0.126301 | Train accuracy: 0.795000 | Test accuracy: 0.774500\n",
"Epoch: 5 | Loss: 0.130105 | Train accuracy: 0.845000 | Test accuracy: 0.813500\n",
"Epoch: 6 | Loss: 0.129739 | Train accuracy: 0.825000 | Test accuracy: 0.789500\n",
"Epoch: 7 | Loss: 0.119317 | Train accuracy: 0.810000 | Test accuracy: 0.785500\n",
"Epoch: 8 | Loss: 0.123790 | Train accuracy: 0.840000 | Test accuracy: 0.801000\n",
"Epoch: 9 | Loss: 0.133677 | Train accuracy: 0.830000 | Test accuracy: 0.794500\n",
"Epoch: 10 | Loss: 0.111080 | Train accuracy: 0.840000 | Test accuracy: 0.808000\n"
]
}
],
"source": [
"# Generate training and test data\n",
"num_training = 200\n",
"num_test = 2000\n",
"\n",
"Xdata, y_train = circle(num_training)\n",
"X_train = np.hstack((Xdata, np.zeros((Xdata.shape[0], 1), requires_grad=False)))\n",
"\n",
"Xtest, y_test = circle(num_test)\n",
"X_test = np.hstack((Xtest, np.zeros((Xtest.shape[0], 1), requires_grad=False)))\n",
"\n",
"\n",
"# Train using Adam optimizer and evaluate the classifier\n",
"num_layers = 3\n",
"learning_rate = 0.6\n",
"epochs = 10\n",
"batch_size = 33\n",
"\n",
"opt = AdamOptimizer(learning_rate, beta1=0.9, beta2=0.999)\n",
"\n",
"# initialize random weights\n",
"params = np.random.uniform(size=(num_layers, 3), requires_grad=True)\n",
"\n",
"predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
"accuracy_train = accuracy_score(y_train, predicted_train)\n",
"\n",
"predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
"accuracy_test = accuracy_score(y_test, predicted_test)\n",
"\n",
"# save predictions with random weights for comparison\n",
"initial_predictions = predicted_test\n",
"\n",
"loss = cost(params, X_test, y_test, state_labels)\n",
"\n",
"print(\n",
" \"Epoch: {:2d} | Cost: {:3f} | Train accuracy: {:3f} | Test Accuracy: {:3f}\".format(\n",
" 0, loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"for it in range(epochs):\n",
" for Xbatch, ybatch in iterate_minibatches(X_train, y_train, batch_size=batch_size):\n",
" params, _, _, _ = opt.step(cost, params, Xbatch, ybatch, state_labels)\n",
"\n",
" predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
" accuracy_train = accuracy_score(y_train, predicted_train)\n",
" loss = cost(params, X_train, y_train, state_labels)\n",
"\n",
" predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
" accuracy_test = accuracy_score(y_test, predicted_test)\n",
" res = [it + 1, loss, accuracy_train, accuracy_test]\n",
" print(\n",
" \"Epoch: {:2d} | Loss: {:3f} | Train accuracy: {:3f} | Test accuracy: {:3f}\".format(\n",
" *res\n",
" )\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "YWspC-9BTnyy"
},
"source": [
"Results\n",
"=======\n"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "f84396a5-9f50-4fe0-b46e-64714c1c9ca2"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.111080 | Train accuracy 0.840000 | Test Accuracy : 0.808000\n",
"Learned weights\n",
"Layer 0: [-0.20678954 1.25626588 -0.26879976]\n",
"Layer 1: [0.6395968 0.4777859 0.36271621]\n",
"Layer 2: [-0.4265417 1.33114344 0.32099705]\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x300 with 3 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"print(\n",
" \"Cost: {:3f} | Train accuracy {:3f} | Test Accuracy : {:3f}\".format(\n",
" loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"print(\"Learned weights\")\n",
"for i in range(num_layers):\n",
" print(\"Layer {}: {}\".format(i, params[i]))\n",
"\n",
"\n",
"fig, axes = plt.subplots(1, 3, figsize=(10, 3))\n",
"plot_data(X_test, initial_predictions, fig, axes[0])\n",
"plot_data(X_test, predicted_test, fig, axes[1])\n",
"plot_data(X_test, y_test, fig, axes[2])\n",
"axes[0].set_title(\"Predictions with random weights\")\n",
"axes[1].set_title(\"Predictions after training\")\n",
"axes[2].set_title(\"True test data\")\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sYQWz6IdTnyy"
},
"source": [
"References\n",
"==========\n",
"\n",
"\\[1\\] Pérez-Salinas, Adrián, et al. \\\"Data re-uploading for a universal\n",
"quantum classifier.\\\" arXiv preprint arXiv:1907.02085 (2019).\n",
"\n",
"\\[2\\] Kingma, Diederik P., and Ba, J. \\\"Adam: A method for stochastic\n",
"optimization.\\\" arXiv preprint arXiv:1412.6980 (2014).\n",
"\n",
"\\[3\\] Liu, Dong C., and Nocedal, J. \\\"On the limited memory BFGS method\n",
"for large scale optimization.\\\" Mathematical programming 45.1-3 (1989):\n",
"503-528.\n",
"\n",
"About the author\n",
"================\n"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since end of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "8FGVwF_QUYza",
"outputId": "88ea807a-f320-4293-e7c1-65ae853ecfbd"
},
"execution_count": 62,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696871167.6202366\n",
"Mon Oct 9 17:06:07 2023\n"
]
}
]
}
],
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